Data & Integration Services Lead | (Agentic AI–Ready) Domain: Human Resources London | Hybrid or Remote | Permanent Up to £125k (Bonus & Benefits) This role will suit a Data & Integration lead with enterprise data architecture and integration design across HR/Payroll estates, governance expertise (data quality, security/privacy, compliance), and a proven track record delivering migration, cutover, and decommissioning. Someone who can bring analytics visualisation (Power BI/Tableau) and semantic modelling, working familiarity with Workday, SAP SuccessFactors, and Oracle HCM, and strong stakeholder management with high-grade documentation and decision papers. Candidates who cannot evidence all of the above in their resumes will not be considered! THE ROLE: You will own the integration landscape and data governance that underpin HR/Payroll transformation and agentic AI. Set standards, industrialise patterns, and make pipelines trustworthy, observable, and compliant so AI agents and analytics deliver value rather than noise. Responsibilities: Design the logical integration landscape (APIs, ETL, events, iPaaS). Define data contracts, lineage, and data quality SLAs ; implement RBAC and security controls. Lead data migration, cutover, and legacy decommissioning/archival. Stand up observability (SLO/SLI, monitoring, runbooks) and support run operations. Enable visualisation frameworks for decision-making. Partner with Enterprise Architecture to align to target state and standards. Support agentic/AI use cases with governed, shareable data. Requirements Enterprise data architecture and integration design across HR/Payroll estates. Governance expertise: data quality, security/privacy, and compliance. Proven delivery across migration, cutover, and decommissioning. Experience with analytics visualisation (Power BI/Tableau) and semantic modelling. Familiarity with Workday/SAP SuccessFactors/Oracle HCM ecosystems. Strong stakeholder management; clear documentation and decision papers. Nice to have iPaaS/MDM tooling; process mining/IDP exposure. Agent lifecycle/orchestration concepts and ML readiness.